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Document type:
A. Lederer; Z. Yang; J. Jiao; S. Hirche
Cooperative Control of Uncertain Multi-Agent Systems via Distributed Gaussian Processes
For single agent systems, probabilistic machine learning techniques such as Gaussian process regression have been shown to be suitable methods for inferring models of unknown nonlinearities, which can be employed to improve the performance of control laws. While this approach can be extended to the cooperative control of multi-agent systems, it leads to a decentralized learning of the unknown nonlinearity, i.e., each agent independently infers a m...    »
data_driven_control; coman
Journal title:
IEEE Transactions on Automatic Control
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